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Record W7104470193 · doi:10.71781/18562

Un modèle d’intervention en violence familiale fondé sur les récits de sortie de la violence d’hommes et de femmes innus et cris

2025· dissertation· fr· W7104470193 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typedissertation
Languagefr
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsSocial mobilizationDemobilizationPoliticsContext (archaeology)Solidarity

Abstract

fetched live from OpenAlex

Cette recherche explore les parcours de sortie de la violence familiale au sein de deux nations autochtones au Québec, en mettant en lumière les effets persistants du colonialisme et des traumatismes intergénérationnels. L’étude se concentre sur les récits d’adultes issus des nations cries et innues, cherchant à dégager les modalités et les fondements nécessaires à l’élaboration d’un modèle d’intervention culturellement sécuritaire. L’analyse des expériences conduit à une critique des modèles d’intervention traditionnels, souvent inefficaces en contextes autochtones, et plaide pour des approches holistiques intégrant les pratiques culturelles, spirituelles et communautaires autochtones. La résilience communautaire et la réappropriation des territoires traditionnels sont identifiées comme des éléments clés du parcours de sortie de la violence. L’importance de l’implication active des communautés autochtones dans le développement des programmes d’intervention est mise de l’avant, afin de créer des solutions sur mesure qui respectent les spécificités culturelles et répondent aux besoins diversifiés de ces populations. Finalement, l’étude propose un modèle d’intervention inspiré par la métaphore de l’arbre de la guérison, capable de s’adapter aux réalités individuelles et culturelles des participants, tout en favorisant un rétablissement durable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.371
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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